premise
string
hypothesis
string
label
int64
| | #ofvideos | Averageframes | Datasetlength | | --- | --- | --- | --- | | UCSDPed1 | 70 | 201 | 5min |
| UCSDPed2 | 28 | 163 | 5min | | --- | --- | --- | --- | | SubwayEntrance | 1 | 121,749 | 1.5hours | | SubwaExit | 1 | 64,901 | 1.5hours | | Avenue | 37 | 839 | 30min | | UMN | 5 | 1290 | 5min | | BOSS | 12 | 4052 | 27min | | Ours | 1900 | 7247 | 128hours |
1
| | #ofvideos | Averageframes | Datasetlength | | --- | --- | --- | --- | | UCSDPed1 | 70 | 201 | 5min |
| Measure | WHdebarking | WHboarding | SGdebarking | SGboarding | | --- | --- | --- | --- | --- | | Passengers | 1800 | 1800 | 1800 | 1800 | | Min | 48s | 62s | 33s | 62s | | Max(=total) | 418s | 558s | 499s | 279s | | Avg | 244s | 181s | 267s | 165s | | Var | 10,061 | 10,376 | 17,460 | 4,107 | | SD | 100 | 102 | 132 | 65 | | 75thperc. | 330s | 221s | 381s | 220s | | 95thperc. | 398s | 440s | 471s | 265s |
0
| | #ofvideos | Averageframes | Datasetlength | | --- | --- | --- | --- | | UCSDPed1 | 70 | 201 | 5min |
| UCSDPed2 | 28 | 163 | 5min | | --- | --- | --- | --- | | SubwayEntrance | 1 | 121,749 | 1.5hours | | SubwaExit | 1 | 64,901 | 1.5hours | | Avenue | 37 | 839 | 30min | | UMN | 5 | 1290 | 5min | | BOSS | 12 | 4052 | 27min | | Ours | 1900 | 7247 | 128hours |
1
| | #ofvideos | Averageframes | Datasetlength | | --- | --- | --- | --- | | UCSDPed1 | 70 | 201 | 5min |
| Var | 10,061 | 10,376 | 17,460 | 4,107 | | --- | --- | --- | --- | --- | | SD | 100 | 102 | 132 | 65 | | 75thperc. | 330s | 221s | 381s | 220s | | 95thperc. | 398s | 440s | 471s | 265s |
0
| Method | Protein | DNA | Music | Sports | | --- | --- | --- | --- | --- | | CGK+SFM(D=128)<br>CGK+FM(D=128) | 7.056(±5.319)<br>7.054(±5.316) | 7.051(±5.318)<br>7.055(±5.322) | 7.059(±5.320)<br>7.059(±5.319) | 7.057(±5.319)<br>7.057(±5.319) | | CGK+SFM(D=512)<br>CGK+FM(D=512) | 3.524(±2.662)<br>3.523(±2.664) | 3.526(±2.663)<br>3.526(±2.664) | 3.526(±2.662)<br>3.527(±2.661) | 3.525(±2.662)<br>3.525(±2.662) | | CGK+SFM(D=2048)<br>CGK+FM(D=2048) | 1.761(±1.331)<br>1.762(±1.332) | 1.762(±1.332)<br>1.761(±1.331) | 1.763(±1.332)<br>1.332(±1.763) | 1.763(±1.332)<br>1.762(±1.331) |
| CGK+SFM(D=8192)<br>CGK+FM(D=8192) | 0.881(±0.662)<br>0.881(±0.666) | 0.881(±0.665)<br>0.881(±0.666) | 0.881(±0.665)<br>0.881(±0.666) | 0.881(±0.665)<br>0.881(±0.665) | | --- | --- | --- | --- | --- | | CGK+SFM(D=16384)<br>CGK+FM(D=16384) | 0.623(±0.471)<br>0.623(±0.471) | 0.623(±0.470)<br>0.623(±0.470) | 0.632(±0.470)<br>0.632(±0.471) | 0.623(±0.470)<br>0.623(±0.470) |
1
| Method | Protein | DNA | Music | Sports | | --- | --- | --- | --- | --- | | CGK+SFM(D=128)<br>CGK+FM(D=128) | 7.056(±5.319)<br>7.054(±5.316) | 7.051(±5.318)<br>7.055(±5.322) | 7.059(±5.320)<br>7.059(±5.319) | 7.057(±5.319)<br>7.057(±5.319) | | CGK+SFM(D=512)<br>CGK+FM(D=512) | 3.524(±2.662)<br>3.523(±2.664) | 3.526(±2.663)<br>3.526(±2.664) | 3.526(±2.662)<br>3.527(±2.661) | 3.525(±2.662)<br>3.525(±2.662) | | CGK+SFM(D=2048)<br>CGK+FM(D=2048) | 1.761(±1.331)<br>1.762(±1.332) | 1.762(±1.332)<br>1.761(±1.331) | 1.763(±1.332)<br>1.332(±1.763) | 1.763(±1.332)<br>1.762(±1.331) |
| Method | Protein | DNA | Music | Sports | | --- | --- | --- | --- | --- | | ESP+SFM(D=128)<br>ESP+FM(D=128) | 7.054(±5.320)<br>7.055(±5.321) | 7.051(±5.318)<br>7.054(±2.664) | 7.058(±5.318)<br>7.059(±5.318) | 7.058(±5.319)<br>7.059(±5.320) | | ESP+SFM(D=512)<br>ESP+FM(D=512) | 3.523(±2.662)<br>3.526(±2.665) | 3.526(±2.663)<br>3.526(±2.666) | 3.526(±2.662)<br>3.526(±2.663) | 3.525(±2.662)<br>3.526(±2.663) | | ESP+SFM(D=2048)<br>ESP+FM(D=2048) | 1.762(±1.332)<br>1.763(±1.332) | 1.762(±1.332)<br>1.762(±1.332) | 1.762(±1.332)<br>1.762(±1.331) | 1.762(±1.332)<br>1.763(±1.331) | | ESP+SFM(D=8192)<br>ESP+FM(D=8192) | 0.881(±0.666)<br>0.880(±0.666) | 0.881(±0.665)<br>0.881(±0.666) | 0.879(±0.665)<br>0.881(±0.666) | 0.881(±0.665)<br>0.881(±0.666) | | ESP+SFM(D=16384)<br>ESP+FM(D=16384) | 0.623(±0.471)<br>0.628(±0.470) | 0.623(±0.470)<br>0.623(±0.471) | 0.621(±0.470)<br>0.623(±0.471) | 0.623(±0.470)<br>0.623(±0.471) |
0
| Method | Protein | DNA | Music | Sports | | --- | --- | --- | --- | --- | | CGK+SFM(D=128)<br>CGK+FM(D=128) | 7.056(±5.319)<br>7.054(±5.316) | 7.051(±5.318)<br>7.055(±5.322) | 7.059(±5.320)<br>7.059(±5.319) | 7.057(±5.319)<br>7.057(±5.319) | | CGK+SFM(D=512)<br>CGK+FM(D=512) | 3.524(±2.662)<br>3.523(±2.664) | 3.526(±2.663)<br>3.526(±2.664) | 3.526(±2.662)<br>3.527(±2.661) | 3.525(±2.662)<br>3.525(±2.662) |
| CGK+SFM(D=2048)<br>CGK+FM(D=2048) | 1.761(±1.331)<br>1.762(±1.332) | 1.762(±1.332)<br>1.761(±1.331) | 1.763(±1.332)<br>1.332(±1.763) | 1.763(±1.332)<br>1.762(±1.331) | | --- | --- | --- | --- | --- | | CGK+SFM(D=8192)<br>CGK+FM(D=8192) | 0.881(±0.662)<br>0.881(±0.666) | 0.881(±0.665)<br>0.881(±0.666) | 0.881(±0.665)<br>0.881(±0.666) | 0.881(±0.665)<br>0.881(±0.665) | | CGK+SFM(D=16384)<br>CGK+FM(D=16384) | 0.623(±0.471)<br>0.623(±0.471) | 0.623(±0.470)<br>0.623(±0.470) | 0.632(±0.470)<br>0.632(±0.471) | 0.623(±0.470)<br>0.623(±0.470) |
1
| Method | Protein | DNA | Music | Sports | | --- | --- | --- | --- | --- | | CGK+SFM(D=128)<br>CGK+FM(D=128) | 7.056(±5.319)<br>7.054(±5.316) | 7.051(±5.318)<br>7.055(±5.322) | 7.059(±5.320)<br>7.059(±5.319) | 7.057(±5.319)<br>7.057(±5.319) | | CGK+SFM(D=512)<br>CGK+FM(D=512) | 3.524(±2.662)<br>3.523(±2.664) | 3.526(±2.663)<br>3.526(±2.664) | 3.526(±2.662)<br>3.527(±2.661) | 3.525(±2.662)<br>3.525(±2.662) |
| ESP+SFM(D=8192)<br>ESP+FM(D=8192) | 0.881(±0.666)<br>0.880(±0.666) | 0.881(±0.665)<br>0.881(±0.666) | 0.879(±0.665)<br>0.881(±0.666) | 0.881(±0.665)<br>0.881(±0.666) | | --- | --- | --- | --- | --- | | ESP+SFM(D=16384)<br>ESP+FM(D=16384) | 0.623(±0.471)<br>0.628(±0.470) | 0.623(±0.470)<br>0.623(±0.471) | 0.621(±0.470)<br>0.623(±0.471) | 0.623(±0.470)<br>0.623(±0.471) |
0
| | ModelcheckingTA | BDIagents | | --- | --- | --- | | CooperativeManufacturingAssistant | | | | Model’slinesofcode<br>No.states(transitions)orplans<br>Modellingtime<br>Modelexplor.time(min/test)<br>Modelexplor.time(max/test) | 725<br>53(72)<br>≈10.5hrs<br>0.001s<br>33.36s | 348<br>79<br>≈6hrs<br>5s<br>5s |
| HomeCareAssistant | | | | --- | --- | --- | | Model’slinesofcode<br>No.states(transitions)orplans<br>Modellingtime<br>Modelexplor.time(min/test)<br>Modelexplor.time(max/test) | 722<br>42(67)<br>≈5.5hrs<br>0.001s<br>2.775s | 131<br>35<br>≈3hrs<br>1s<br>1s |
1
| | ModelcheckingTA | BDIagents | | --- | --- | --- | | CooperativeManufacturingAssistant | | | | Model’slinesofcode<br>No.states(transitions)orplans<br>Modellingtime<br>Modelexplor.time(min/test)<br>Modelexplor.time(max/test) | 725<br>53(72)<br>≈10.5hrs<br>0.001s<br>33.36s | 348<br>79<br>≈6hrs<br>5s<br>5s |
| | Human | Robot | Pseudorandom | ModelcheckingTA | BDIagents | | --- | --- | --- | --- | --- | --- | | CooperativeManufacturingAssistant(160testspermethod) | | | | | | | 1<br>2<br>3 | 4legs<br>4legs<br>4legsandbored | GPL=(1,1,1)foratleast1leg<br>GPL(cid:54)=(1,1,1)foratleast1leg<br>Timedoutatleastonce | 0<br>0<br>2 | 24<br>30<br>43 | 24<br>31<br>32 | | 4<br>5<br>6 | 3legs<br>3legs<br>3legsandbored | GPL=(1,1,1)foratleast1leg<br>GPL(cid:54)=(1,1,1)foratleast1leg<br>Timedoutatleastonce | 0<br>7<br>10 | 20<br>38<br>38 | 12<br>22<br>27 | | 7<br>8<br>9 | 2legs<br>2legs<br>2legsandbored | GPL=(1,1,1)foratleast1leg<br>GPL(cid:54)=(1,1,1)foratleast1leg<br>Timedoutatleastonce | 2<br>6<br>9 | 13<br>28<br>11 | 5<br>10<br>7 | | 10<br>11<br>12 | 1leg<br>1leg<br>1leg | GPL=(1,1,1)<br>GPL(cid:54)=(1,1,1)<br>Timedout | 14<br>10<br>10 | 11<br>14<br>2 | 9<br>14<br>1 | | 13<br>14 | 1to4legs<br>Nolegorbored | Alwaystimedout<br>Alwaystimedout | 72<br>62 | 38<br>2 | 75<br>3 | | HomeCareAssistant(50testspermethod) | | | | | | | 1<br>2<br>3<br>4 | Atleast1feed<br>Atleast1clean<br>Atleast1fridge<br>Atleast1sink | Atleast1feed<br>Atleast1clean<br>Atleast1fridge<br>Atleast1sink | 5<br>14<br>4<br>8 | 9<br>3<br>12<br>2 | 6<br>14<br>4<br>9 | | 5 | Atleast2feedorclean | Atleast2feedorclean | 5 | 22 | 5 | | 6 | Othercommands | Idle | 13 | 2 | 12 |
0
| | ModelcheckingTA | BDIagents | | --- | --- | --- | | CooperativeManufacturingAssistant | | |
| Model’slinesofcode<br>No.states(transitions)orplans<br>Modellingtime<br>Modelexplor.time(min/test)<br>Modelexplor.time(max/test) | 725<br>53(72)<br>≈10.5hrs<br>0.001s<br>33.36s | 348<br>79<br>≈6hrs<br>5s<br>5s | | --- | --- | --- | | HomeCareAssistant | | | | Model’slinesofcode<br>No.states(transitions)orplans<br>Modellingtime<br>Modelexplor.time(min/test)<br>Modelexplor.time(max/test) | 722<br>42(67)<br>≈5.5hrs<br>0.001s<br>2.775s | 131<br>35<br>≈3hrs<br>1s<br>1s |
1
| | ModelcheckingTA | BDIagents | | --- | --- | --- | | CooperativeManufacturingAssistant | | |
| 1<br>2<br>3 | 4legs<br>4legs<br>4legsandbored | GPL=(1,1,1)foratleast1leg<br>GPL(cid:54)=(1,1,1)foratleast1leg<br>Timedoutatleastonce | 0<br>0<br>2 | 24<br>30<br>43 | 24<br>31<br>32 | | --- | --- | --- | --- | --- | --- | | 4<br>5<br>6 | 3legs<br>3legs<br>3legsandbored | GPL=(1,1,1)foratleast1leg<br>GPL(cid:54)=(1,1,1)foratleast1leg<br>Timedoutatleastonce | 0<br>7<br>10 | 20<br>38<br>38 | 12<br>22<br>27 | | 7<br>8<br>9 | 2legs<br>2legs<br>2legsandbored | GPL=(1,1,1)foratleast1leg<br>GPL(cid:54)=(1,1,1)foratleast1leg<br>Timedoutatleastonce | 2<br>6<br>9 | 13<br>28<br>11 | 5<br>10<br>7 | | 10<br>11<br>12 | 1leg<br>1leg<br>1leg | GPL=(1,1,1)<br>GPL(cid:54)=(1,1,1)<br>Timedout | 14<br>10<br>10 | 11<br>14<br>2 | 9<br>14<br>1 | | 13<br>14 | 1to4legs<br>Nolegorbored | Alwaystimedout<br>Alwaystimedout | 72<br>62 | 38<br>2 | 75<br>3 | | HomeCareAssistant(50testspermethod) | | | | | | | 1<br>2<br>3<br>4 | Atleast1feed<br>Atleast1clean<br>Atleast1fridge<br>Atleast1sink | Atleast1feed<br>Atleast1clean<br>Atleast1fridge<br>Atleast1sink | 5<br>14<br>4<br>8 | 9<br>3<br>12<br>2 | 6<br>14<br>4<br>9 | | 5 | Atleast2feedorclean | Atleast2feedorclean | 5 | 22 | 5 | | 6 | Othercommands | Idle | 13 | 2 | 12 |
0
| Command | ANumber | Comments | | --- | --- | --- | | \alignauthor | 100 | Authoralignment | | \numberofauthors | 200 | Authorenumeration |
| \table | 300 | Fortables | | --- | --- | --- | | \table* | 400 | Forwidertables |
1
| Command | ANumber | Comments | | --- | --- | --- | | \alignauthor | 100 | Authoralignment | | \numberofauthors | 200 | Authorenumeration |
| Command | ANumber | Comments | | --- | --- | --- | | \alignauthor | 100 | Authoralignment | | \numberofauthors | 200 | Authorenumeration | | \table | 300 | Fortables | | \table* | 400 | Forwidertables |
0
| Command | ANumber | Comments | | --- | --- | --- | | \alignauthor | 100 | Authoralignment | | \numberofauthors | 200 | Authorenumeration |
| \table | 300 | Fortables | | --- | --- | --- | | \table* | 400 | Forwidertables |
1
| Command | ANumber | Comments | | --- | --- | --- | | \alignauthor | 100 | Authoralignment | | \numberofauthors | 200 | Authorenumeration |
| \numberofauthors | 200 | Authorenumeration | | --- | --- | --- | | \table | 300 | Fortables | | \table* | 400 | Forwidertables |
0
| | Algorithm | H.264 | JP2K | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | | LCC | SROCC | RMSE | LCC | SROCC | RMSE | | | | VQUEMODES | SBIQE | 0.9262 | 0.8956 | 0.3286 | 0.9706 | 0.9473 | 0.2415 |
| BRISQUE | 0.9517 | 0.9323 | 0.2319 | 0.9809 | 0.9577 | 0.1097 | | --- | --- | --- | --- | --- | --- | --- | | NIQE | 0.9594 | 0.9439 | 0.1791 | 0.9859 | 0.9666 | 0.0912 |
1
| | Algorithm | H.264 | JP2K | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | | LCC | SROCC | RMSE | LCC | SROCC | RMSE | | | | VQUEMODES | SBIQE | 0.9262 | 0.8956 | 0.3286 | 0.9706 | 0.9473 | 0.2415 |
| Algorithm | H.264 | JP2K | | | | | | --- | --- | --- | --- | --- | --- | --- | | LCC | SROCC | RMSE | LCC | SROCC | RMSE | | | SSIM | 0.7674 | 0.5464 | 0.8843 | 0.7283 | 0.5974 | 0.9202 | | MS-SSIM | 0.8795 | 0.6673 | 0.6955 | 0.9414 | 0.9299 | 0.4327 | | SBIQE | 0.0062 | 0.0058 | 1.9856 | 0.0120 | 0.0574 | 1.0289 | | BRISQUE | 0.7915 | 0.7637 | 0.7912 | 0.8048 | 0.8999 | 0.5687 | | NIQE | 0.6814 | 0.6412 | 0.8715 | 0.6558 | 0.6427 | 0.7157 | | STMAD | 0.7641 | 0.7354 | 0.7296 | 0.8388 | 0.7236 | 0.7136 | | FLOSIM | 0.9265 | 0.8987 | 0.4256 | 0.9665 | 0.9495 | 0.3359 | | Chenetal. | 0.6618 | 0.5720 | 0.6915 | 0.8723 | 0.8724 | 0.6182 | | STRIQE | 0.7430 | 0.7167 | 0.8433 | 0.8403 | 0.8175 | 0.5666 | | VQUEMODES(NIQE) | 0.9594 | 0.9439 | 0.1791 | 0.9859 | 0.9666 | 0.0912 |
0
| | Algorithm | H.264 | JP2K | | | | --- | --- | --- | --- | --- | --- | | LCC | SROCC | RMSE | LCC | SROCC | RMSE |
| VQUEMODES | SBIQE | 0.9262 | 0.8956 | 0.3286 | 0.9706 | 0.9473 | 0.2415 | | --- | --- | --- | --- | --- | --- | --- | --- | | BRISQUE | 0.9517 | 0.9323 | 0.2319 | 0.9809 | 0.9577 | 0.1097 | | | NIQE | 0.9594 | 0.9439 | 0.1791 | 0.9859 | 0.9666 | 0.0912 | |
1
| | Algorithm | H.264 | JP2K | | | | --- | --- | --- | --- | --- | --- | | LCC | SROCC | RMSE | LCC | SROCC | RMSE |
| STMAD | 0.7641 | 0.7354 | 0.7296 | 0.8388 | 0.7236 | 0.7136 | | --- | --- | --- | --- | --- | --- | --- | | FLOSIM | 0.9265 | 0.8987 | 0.4256 | 0.9665 | 0.9495 | 0.3359 | | Chenetal. | 0.6618 | 0.5720 | 0.6915 | 0.8723 | 0.8724 | 0.6182 | | STRIQE | 0.7430 | 0.7167 | 0.8433 | 0.8403 | 0.8175 | 0.5666 | | VQUEMODES(NIQE) | 0.9594 | 0.9439 | 0.1791 | 0.9859 | 0.9666 | 0.0912 |
0
| method | 0 | 1 | 2 | 3 | 4 | 5 | | --- | --- | --- | --- | --- | --- | --- | | RND | 0.590 | 0.677 | 0.714 | 0.736 | 0.749 | 0.758 | | AC | 0.590 | 0.677 | 0.713 | 0.735 | 0.748 | 0.757 | | ACG | 0.590 | 0.678 | 0.717 | 0.741 | 0.754 | 0.760 | | NFQ | 0.590 | 0.677 | 0.713 | 0.736 | 0.750 | 0.758 |
| NFQG | 0.590 | 0.688 | 0.717 | 0.738 | 0.748 | 0.758 | | --- | --- | --- | --- | --- | --- | --- | | LSTM | 0.590 | 0.694 | 0.732 | 0.746 | 0.754 | 0.757 | | LSTM-i2 | 0.614 | 0.715 | 0.751 | 0.769 | 0.778 | 0.785 | | LSTM-i3 | 0.617 | 0.718 | 0.758 | 0.776 | 0.790 | 0.793 |
1
| method | 0 | 1 | 2 | 3 | 4 | 5 | | --- | --- | --- | --- | --- | --- | --- | | RND | 0.590 | 0.677 | 0.714 | 0.736 | 0.749 | 0.758 | | AC | 0.590 | 0.677 | 0.713 | 0.735 | 0.748 | 0.757 | | ACG | 0.590 | 0.678 | 0.717 | 0.741 | 0.754 | 0.760 | | NFQ | 0.590 | 0.677 | 0.713 | 0.736 | 0.750 | 0.758 |
| N | 1 | 2 | 5 | 10 | 20 | 100 | | --- | --- | --- | --- | --- | --- | --- | | Situate | 0.37(0.09) | 0.50(0.07) | 0.56(0.07) | 0.65(0.04) | 0.77(0.05) | 0.93(0.02) | | Uniform | 0.29(0.07)) | 0.32(0.07) | 0.44(0.06) | 0.54(0.04) | 0.65(0.03) | 0.79(0.03) | | Faster-RCNN | 0.24 | 0.25 | 0.28 | 0.38 | 0.54 | 0.91 | | IRSG | 0.24 | 0.24 | 0.27 | 0.37 | 0.55 | 0.87 |
0
| method | 0 | 1 | 2 | 3 | 4 | 5 | | --- | --- | --- | --- | --- | --- | --- | | RND | 0.590 | 0.677 | 0.714 | 0.736 | 0.749 | 0.758 | | AC | 0.590 | 0.677 | 0.713 | 0.735 | 0.748 | 0.757 | | ACG | 0.590 | 0.678 | 0.717 | 0.741 | 0.754 | 0.760 | | NFQ | 0.590 | 0.677 | 0.713 | 0.736 | 0.750 | 0.758 | | NFQG | 0.590 | 0.688 | 0.717 | 0.738 | 0.748 | 0.758 |
| LSTM | 0.590 | 0.694 | 0.732 | 0.746 | 0.754 | 0.757 | | --- | --- | --- | --- | --- | --- | --- | | LSTM-i2 | 0.614 | 0.715 | 0.751 | 0.769 | 0.778 | 0.785 | | LSTM-i3 | 0.617 | 0.718 | 0.758 | 0.776 | 0.790 | 0.793 |
1
| method | 0 | 1 | 2 | 3 | 4 | 5 | | --- | --- | --- | --- | --- | --- | --- | | RND | 0.590 | 0.677 | 0.714 | 0.736 | 0.749 | 0.758 | | AC | 0.590 | 0.677 | 0.713 | 0.735 | 0.748 | 0.757 | | ACG | 0.590 | 0.678 | 0.717 | 0.741 | 0.754 | 0.760 | | NFQ | 0.590 | 0.677 | 0.713 | 0.736 | 0.750 | 0.758 | | NFQG | 0.590 | 0.688 | 0.717 | 0.738 | 0.748 | 0.758 |
| Uniform | 0.29(0.07)) | 0.32(0.07) | 0.44(0.06) | 0.54(0.04) | 0.65(0.03) | 0.79(0.03) | | --- | --- | --- | --- | --- | --- | --- | | Faster-RCNN | 0.24 | 0.25 | 0.28 | 0.38 | 0.54 | 0.91 | | IRSG | 0.24 | 0.24 | 0.27 | 0.37 | 0.55 | 0.87 |
0
| CNNmodel | Layer | Activations | Encoding | | --- | --- | --- | --- | | AlexNet | Conv5 | (13,13,256) | FV+PCA |
| AlexNet | Conv5 | (13,13,256) | VLAD+PCA | | --- | --- | --- | --- | | AlexNet | FC7 | 4096 | − | | GoogLeNet | Inc.5b | (7,7,1024) | VLAD+PCA | | GoogLeNet | Pool5 | 1024 | − |
1
| CNNmodel | Layer | Activations | Encoding | | --- | --- | --- | --- | | AlexNet | Conv5 | (13,13,256) | FV+PCA |
| CNN | Imageresolution | RunTime(ms) | | --- | --- | --- | | AlexNet | 227×227 | 2.3 | | VGG16 | 224×224 | 10 | | Resnet50 | 224×224 | 17 | | SqueezeNet | 224×224 | 2.5 | | SqueezeNet | 448×448 | 4 | | SqueezeNet | 625×625 | 6 |
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| CNNmodel | Layer | Activations | Encoding | | --- | --- | --- | --- | | AlexNet | Conv5 | (13,13,256) | FV+PCA |
| AlexNet | Conv5 | (13,13,256) | VLAD+PCA | | --- | --- | --- | --- | | AlexNet | FC7 | 4096 | − | | GoogLeNet | Inc.5b | (7,7,1024) | VLAD+PCA | | GoogLeNet | Pool5 | 1024 | − |
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| CNNmodel | Layer | Activations | Encoding | | --- | --- | --- | --- | | AlexNet | Conv5 | (13,13,256) | FV+PCA |
| SqueezeNet | 448×448 | 4 | | --- | --- | --- | | SqueezeNet | 625×625 | 6 |
0
| Hyper-parameters | Value | | --- | --- | | Learningrate | 0.00015822 | | Beta | 0.000076253698849 | | Dropout | 0.85565561 | | Networkparameters | Value | | RegularizationType | L2 |
| BatchSize | 256 | | --- | --- | | WeightUpdate | AdamOptimization |
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| Hyper-parameters | Value | | --- | --- | | Learningrate | 0.00015822 | | Beta | 0.000076253698849 | | Dropout | 0.85565561 | | Networkparameters | Value | | RegularizationType | L2 |
| Parameters | Value | | --- | --- | | Maximumsentencelength | 15words | | OptimizationMethod | Adam | | Learningrate | 0.01 | | Batchsize | 256 | | LSTMParameters | Uniformdistributionfrom[-0.1,0.1] |
0
| Hyper-parameters | Value | | --- | --- | | Learningrate | 0.00015822 |
| Beta | 0.000076253698849 | | --- | --- | | Dropout | 0.85565561 | | Networkparameters | Value | | RegularizationType | L2 | | BatchSize | 256 | | WeightUpdate | AdamOptimization |
1
| Hyper-parameters | Value | | --- | --- | | Learningrate | 0.00015822 |
| OptimizationMethod | Adam | | --- | --- | | Learningrate | 0.01 | | Batchsize | 256 | | LSTMParameters | Uniformdistributionfrom[-0.1,0.1] |
0
| Method | MAE | MSE | | --- | --- | --- | | HF | 3.51 | 18.70 |
| SPPF | 3.47 | 17.46 | | --- | --- | --- | | LFV | 3.37 | 18.14 | | ourmethod | 2.41 | 9.12 |
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| Method | MAE | MSE | | --- | --- | --- | | HF | 3.51 | 18.70 |
| PartA | | | | --- | --- | --- | | MAE | MSE | MAE | | 83.1 | 120.4 | 20.1 | | 75.9 | 109.2 | 16.5 | | 72.9 | 103.1 | 14.6 | | 69.3 | 96.4 | 11.6 |
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| Method | MAE | MSE | | --- | --- | --- | | HF | 3.51 | 18.70 | | SPPF | 3.47 | 17.46 |
| LFV | 3.37 | 18.14 | | --- | --- | --- | | ourmethod | 2.41 | 9.12 |
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| Method | MAE | MSE | | --- | --- | --- | | HF | 3.51 | 18.70 | | SPPF | 3.47 | 17.46 |
| 75.9 | 109.2 | 16.5 | | --- | --- | --- | | 72.9 | 103.1 | 14.6 | | 69.3 | 96.4 | 11.6 |
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| | CNN | DailyMail | | | | --- | --- | --- | --- | --- | | Models | Val | Test | Val | Test | | L2RReader | 64.3 | 65.8 | 69.1 | 67.3 |
| L2R+Coref | 63.8 | 64.8 | 68.3 | 66.5 | | --- | --- | --- | --- | --- | | L2R-WMD | 60.8 | 61.5 | 63.2 | 61.6 | | L2R-FS | 61.5 | 62.5 | 65.3 | 63.7 |
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| | CNN | DailyMail | | | | --- | --- | --- | --- | --- | | Models | Val | Test | Val | Test | | L2RReader | 64.3 | 65.8 | 69.1 | 67.3 |
| | CNN | Dailymail | | | | --- | --- | --- | --- | --- | | #Training | Val | Test | Val | Test | | 10 | 35.2 | 41.6 | 45.7 | 43.6 | | 20 | 57.4 | 55.1 | 57.2 | 56.2 | | 30 | 56.7 | 60.2 | 61.4 | 60.3 | | 40 | 57 | 60 | 62.3 | 61.3 | | 50 | 60.3 | 63.1 | 63.5 | 62.5 | | 100 | 61.5 | 63.9 | 65.4 | 64.6 | | 200 | 62.5 | 64.9 | 67.3 | 65.2 | | 500 | 62.8 | 65 | 67.5 | 66.3 | | 1000 | 62.9 | 65.2 | 68.3 | 66.7 | | 2000 | 63.2 | 65.2 | 69.0 | 67.3 | | 5000 | 64.3 | 65.8 | 69.1 | 67.3 |
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| | CNN | DailyMail | | | | --- | --- | --- | --- | --- | | Models | Val | Test | Val | Test | | L2RReader | 64.3 | 65.8 | 69.1 | 67.3 |
| L2R+Coref | 63.8 | 64.8 | 68.3 | 66.5 | | --- | --- | --- | --- | --- | | L2R-WMD | 60.8 | 61.5 | 63.2 | 61.6 | | L2R-FS | 61.5 | 62.5 | 65.3 | 63.7 |
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| | CNN | DailyMail | | | | --- | --- | --- | --- | --- | | Models | Val | Test | Val | Test | | L2RReader | 64.3 | 65.8 | 69.1 | 67.3 |
| 30 | 56.7 | 60.2 | 61.4 | 60.3 | | --- | --- | --- | --- | --- | | 40 | 57 | 60 | 62.3 | 61.3 | | 50 | 60.3 | 63.1 | 63.5 | 62.5 | | 100 | 61.5 | 63.9 | 65.4 | 64.6 | | 200 | 62.5 | 64.9 | 67.3 | 65.2 | | 500 | 62.8 | 65 | 67.5 | 66.3 | | 1000 | 62.9 | 65.2 | 68.3 | 66.7 | | 2000 | 63.2 | 65.2 | 69.0 | 67.3 | | 5000 | 64.3 | 65.8 | 69.1 | 67.3 |
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| testset | BLEU | | --- | --- | | Random1000samples | 11.85 |
| Withidioms | 6.35 | | --- | --- | | Blacklisttriggered | 5.64 | | Blacklistnottriggered | 6.44 |
1
| testset | BLEU | | --- | --- | | Random1000samples | 11.85 |
| | RegExLib | Snort | | --- | --- | --- | | Totalpatterns | 2994 | 12499 | | Analyzable(onlyregularconstructs) | 2213 | 9408 | | UsesKleenestar | 1103 | 2741 | | PumpableKleeneandsuffixfound | 127 | 15 | | PumpableKleeneonly | 20 | 4 | | NopumpableKleene | 2066 | 9389 | | MaxHFπsteps | 509 | 256 | | Totalclassificationtime<br>(IntelCore2Duo1.8MHz,4GBRAM) | 40s | 10s |
0
| testset | BLEU | | --- | --- | | Random1000samples | 11.85 | | Withidioms | 6.35 |
| Blacklisttriggered | 5.64 | | --- | --- | | Blacklistnottriggered | 6.44 |
1
| testset | BLEU | | --- | --- | | Random1000samples | 11.85 | | Withidioms | 6.35 |
| MaxHFπsteps | 509 | 256 | | --- | --- | --- | | Totalclassificationtime<br>(IntelCore2Duo1.8MHz,4GBRAM) | 40s | 10s |
0
| Device | GTX560Ti | GTX780 | GTX980 | | --- | --- | --- | --- | | W(byte/cycle)bank | 2 | 8 | 4 | | f(GHz)core | 0.950 | 1.006 | 1.279 |
| W(GB/s)SM | 60.80 | 257.54 | 163.84 | | --- | --- | --- | --- | | (cid:48)<br>(GB/s)W<br>SM | 34.90 | 83.81 | 137.41 |
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| Device | GTX560Ti | GTX780 | GTX980 | | --- | --- | --- | --- | | W(byte/cycle)bank | 2 | 8 | 4 | | f(GHz)core | 0.950 | 1.006 | 1.279 |
| GPU | GTX1080 | TitanX | | --- | --- | --- | | ComputeCapability | 6.1 | 6.1 | | GlobalMem(GB) | 8 | 10 | | #ofSMs | 20 | 28 | | CoreClock(MHz) | 1607 | 1417 | | MemClock(MHz) | 5005 | 5005 | | MemBusWidth | 256 | 384 | | L2Cache(KB) | 2048 | 3072 |
0
| Device | GTX560Ti | GTX780 | GTX980 | | --- | --- | --- | --- | | W(byte/cycle)bank | 2 | 8 | 4 | | f(GHz)core | 0.950 | 1.006 | 1.279 |
| W(GB/s)SM | 60.80 | 257.54 | 163.84 | | --- | --- | --- | --- | | (cid:48)<br>(GB/s)W<br>SM | 34.90 | 83.81 | 137.41 |
1
| Device | GTX560Ti | GTX780 | GTX980 | | --- | --- | --- | --- | | W(byte/cycle)bank | 2 | 8 | 4 | | f(GHz)core | 0.950 | 1.006 | 1.279 |
| CoreClock(MHz) | 1607 | 1417 | | --- | --- | --- | | MemClock(MHz) | 5005 | 5005 | | MemBusWidth | 256 | 384 | | L2Cache(KB) | 2048 | 3072 |
0
| Model | k=200 | k=300 | k=400 | | --- | --- | --- | --- | | Bag-of-Words-10K | 0.127 | 0.113 | 0.111 | | Single-10k | 0.168 | 0.172 | 0.165 |
| Joint-10k | 0.190 | 0.177 | 0.181 | | --- | --- | --- | --- | | Bag-of-Words-50K | 0.196 | 0.191 | 0.21 | | Single-50k | 0.218 | 0.228 | 0.222 | | Joint-50k | 0.256 | 0.250 | 0.227 | | Bag-of-Words-100K | 0.222 | 0.18 | 0.16 | | Single-100k | 0.225 | 0.218 | 0.199 | | Joint-100k | 0.283 | 0.256 | 0.222 |
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| Model | k=200 | k=300 | k=400 | | --- | --- | --- | --- | | Bag-of-Words-10K | 0.127 | 0.113 | 0.111 | | Single-10k | 0.168 | 0.172 | 0.165 |
| Model | k=200 | k=300 | k=400 | | --- | --- | --- | --- | | Bag-of-Words-10K | 0.457 | 0.445 | 0.483 | | Single-10k | 0.623 | 0.647 | 0.641 | | Joint-10k | 0.650 | 0.636 | 0.635 | | Bag-of-Words-50K | 0.44 | 0.453 | 0.407 | | Single-50k | 0.492 | 0.486 | 0.534 | | Joint-50k | 0.571 | 0.591 | 0.613 | | Bag-of-Words-100K | 0.335 | 0.324 | 0.322 | | Single-100k | 0.431 | 0.413 | 0.456 | | Joint-100k | 0.495 | 0.518 | 0.507 |
0
| Model | k=200 | k=300 | k=400 | | --- | --- | --- | --- | | Bag-of-Words-10K | 0.127 | 0.113 | 0.111 | | Single-10k | 0.168 | 0.172 | 0.165 | | Joint-10k | 0.190 | 0.177 | 0.181 | | Bag-of-Words-50K | 0.196 | 0.191 | 0.21 | | Single-50k | 0.218 | 0.228 | 0.222 |
| Joint-50k | 0.256 | 0.250 | 0.227 | | --- | --- | --- | --- | | Bag-of-Words-100K | 0.222 | 0.18 | 0.16 | | Single-100k | 0.225 | 0.218 | 0.199 | | Joint-100k | 0.283 | 0.256 | 0.222 |
1
| Model | k=200 | k=300 | k=400 | | --- | --- | --- | --- | | Bag-of-Words-10K | 0.127 | 0.113 | 0.111 | | Single-10k | 0.168 | 0.172 | 0.165 | | Joint-10k | 0.190 | 0.177 | 0.181 | | Bag-of-Words-50K | 0.196 | 0.191 | 0.21 | | Single-50k | 0.218 | 0.228 | 0.222 |
| Bag-of-Words-50K | 0.44 | 0.453 | 0.407 | | --- | --- | --- | --- | | Single-50k | 0.492 | 0.486 | 0.534 | | Joint-50k | 0.571 | 0.591 | 0.613 | | Bag-of-Words-100K | 0.335 | 0.324 | 0.322 | | Single-100k | 0.431 | 0.413 | 0.456 | | Joint-100k | 0.495 | 0.518 | 0.507 |
0
| ShapeBasedFeature | | | --- | --- | | 1.Volume | 9.Maximum2Ddiameter(coronal) |
| 2.Surfacearea | 10.Maximum2Ddiameter(sagital) | | --- | --- | | 3.SurfaceareatoVolumeRatio | 11.MajorAxis | | 4.Sphericity | 12.MinorAxis | | 5.SphericalDisproportion | 13.LeastAxis | | 6.Compactness1 | 14.Elongation | | 7.Maximum3Ddiameter | 15.Flatness | | 8.Maximum2Ddiameter(axial) | 16.Compactness2 |
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| ShapeBasedFeature | | | --- | --- | | 1.Volume | 9.Maximum2Ddiameter(coronal) |
| | Aspectratio | Convexity | HScircularity | Solidity | | --- | --- | --- | --- | --- | | Blocky | 0.71±0.13 | 0.99±0.02 | 0.71±0.06 | 0.85±0.02 | | Vesicular | 0.69±0.13 | 0.87±0.05 | 0.48±0.08 | 0.73±0.09 | | Elongated | 0.37±0.06 | 0.96±0.09 | 0.51±0.08 | 0.80±0.23 | | Rounded | 0.80±0.09 | 0.99±0.01 | 0.82±0.04 | 0.89±0.01 |
0
| ShapeBasedFeature | | | --- | --- | | 1.Volume | 9.Maximum2Ddiameter(coronal) | | 2.Surfacearea | 10.Maximum2Ddiameter(sagital) | | 3.SurfaceareatoVolumeRatio | 11.MajorAxis | | 4.Sphericity | 12.MinorAxis | | 5.SphericalDisproportion | 13.LeastAxis | | 6.Compactness1 | 14.Elongation |
| 7.Maximum3Ddiameter | 15.Flatness | | --- | --- | | 8.Maximum2Ddiameter(axial) | 16.Compactness2 |
1
| ShapeBasedFeature | | | --- | --- | | 1.Volume | 9.Maximum2Ddiameter(coronal) | | 2.Surfacearea | 10.Maximum2Ddiameter(sagital) | | 3.SurfaceareatoVolumeRatio | 11.MajorAxis | | 4.Sphericity | 12.MinorAxis | | 5.SphericalDisproportion | 13.LeastAxis | | 6.Compactness1 | 14.Elongation |
| Elongated | 0.37±0.06 | 0.96±0.09 | 0.51±0.08 | 0.80±0.23 | | --- | --- | --- | --- | --- | | Rounded | 0.80±0.09 | 0.99±0.01 | 0.82±0.04 | 0.89±0.01 |
0
| Conv1 | 96×7×7,st.2,pad0 | | --- | --- | | Conv2 | 256×5×5,st.1,pad1 | | Conv3 | 512×3×3,st.1,pad1 | | Conv4 | 512×3×3,st.1,pad1 | | Conv5 | 512×3×3,st.1,pad1 |
| Full6 | 4096dropout | | --- | --- | | Full7 | 4096dropout | | Full8 | 1000softmax |
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| Conv1 | 96×7×7,st.2,pad0 | | --- | --- | | Conv2 | 256×5×5,st.1,pad1 | | Conv3 | 512×3×3,st.1,pad1 | | Conv4 | 512×3×3,st.1,pad1 | | Conv5 | 512×3×3,st.1,pad1 |
| Name | Kernel | OutputSize | Name | Kernel | OutputSize | | --- | --- | --- | --- | --- | --- | | conv1,2 | 3×3 | 320×448×64 | deconv5 | 2×2 | 40×56×256 | | pool1 | 2×2 | 160×224×64 | refine-1convs | 3×3 | 40×56×256 | | conv3,4 | 3×3 | 160×224×128 | deconv4 | 2×2 | 80×112×128 | | pool2 | 2×2 | 80×112×128 | refine-2convs | 3×3 | 80×112×128 | | conv5,6,1-2 | 3×3 | 80×112×256 | deconv3 | 2×2 | 160×224×64 | | pool3 | 2×2 | 40×56×256 | refine-3convs | 3×3 | 160×224×64 | | conv7,8,1-2 | 3×3 | 40×56×512 | deconv2 | 2×2 | 320×448×32 | | pool4 | 2×2 | 20×28×512 | refine-4convs | 3×3 | 320×448×32 |
0
| Conv1 | 96×7×7,st.2,pad0 | | --- | --- | | Conv2 | 256×5×5,st.1,pad1 |
| Conv3 | 512×3×3,st.1,pad1 | | --- | --- | | Conv4 | 512×3×3,st.1,pad1 | | Conv5 | 512×3×3,st.1,pad1 | | Full6 | 4096dropout | | Full7 | 4096dropout | | Full8 | 1000softmax |
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| Conv1 | 96×7×7,st.2,pad0 | | --- | --- | | Conv2 | 256×5×5,st.1,pad1 |
| pool3 | 2×2 | 40×56×256 | refine-3convs | 3×3 | 160×224×64 | | --- | --- | --- | --- | --- | --- | | conv7,8,1-2 | 3×3 | 40×56×512 | deconv2 | 2×2 | 320×448×32 | | pool4 | 2×2 | 20×28×512 | refine-4convs | 3×3 | 320×448×32 |
0
| | Chicago | Paris | Zurich | | | | | --- | --- | --- | --- | --- | --- | --- | | | (15.7h) | Ours(10.5h) | (18.3h) | Ours(7.6h) | (15.5h) | Ours(6.2h) | | Faverage1 | 0.840 | 0.855 | 0.774 | 0.776 | 0.804 | 0.810 |
| Fbuilding1 | 0.823 | 0.837 | 0.821 | 0.822 | 0.824 | 0.823 | | --- | --- | --- | --- | --- | --- | --- | | Froad1 | 0.821 | 0.843 | 0.741 | 0.746 | 0.695 | 0.707 | | Fbackground1 | 0.849 | 0.861 | 0.754 | 0.754 | 0.894 | 0.891 |
1
| | Chicago | Paris | Zurich | | | | | --- | --- | --- | --- | --- | --- | --- | | | (15.7h) | Ours(10.5h) | (18.3h) | Ours(7.6h) | (15.5h) | Ours(6.2h) | | Faverage1 | 0.840 | 0.855 | 0.774 | 0.776 | 0.804 | 0.810 |
| | Gradual | Sharp | | | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Video | #T | TP | FP | FN | P | R | F | #T | TP | FP | FN | P | | 1004ABCa | 203 | 177 | 9 | 26 | 0.952 | 0.872 | 0.91 | 224 | 209 | 18 | 15 | 0.921 | | 1012CNNa | 170 | 149 | 23 | 21 | 0.866 | 0.876 | 0.871 | 215 | 191 | 13 | 24 | 0.936 | | 1016CNNa | 150 | 122 | 13 | 28 | 0.904 | 0.813 | 0.856 | 242 | 211 | 12 | 31 | 0.946 | | 1021ABCa | 175 | 154 | 22 | 21 | 0.875 | 0.88 | 0.877 | 240 | 227 | 14 | 13 | 0.942 | | 1101CNNa | 204 | 187 | 13 | 17 | 0.935 | 0.917 | 0.926 | 191 | 180 | 12 | 11 | 0.938 | | 1109ABCa | 170 | 159 | 12 | 11 | 0.93 | 0.935 | 0.933 | 257 | 241 | 11 | 16 | 0.956 | | 1123CNNa | 126 | 99 | 32 | 27 | 0.756 | 0.786 | 0.77 | 236 | 206 | 8 | 30 | 0.963 | | 1126ABCa | 189 | 179 | 16 | 10 | 0.918 | 0.947 | 0.932 | 273 | 260 | 14 | 13 | 0.949 | | 1208CNNa | 137 | 117 | 22 | 20 | 0.842 | 0.854 | 0.848 | 212 | 192 | 17 | 20 | 0.919 | | 1210ABCa | 159 | 148 | 21 | 11 | 0.876 | 0.931 | 0.902 | 271 | 251 | 7 | 20 | 0.973 | | 1216CNNa | 153 | 137 | 25 | 16 | 0.846 | 0.895 | 0.87 | 197 | 184 | 21 | 13 | 0.898 | | 1221ABCa | 195 | 168 | 18 | 27 | 0.903 | 0.862 | 0.882 | 217 | 195 | 13 | 22 | 0.938 | | Total | 2031 | 1796 | 226 | 235 | 0.888 | 0.884 | 0.886 | 2775 | 2547 | 160 | 228 | 0.941 |
0
| | Chicago | Paris | Zurich | | | | | --- | --- | --- | --- | --- | --- | --- | | | (15.7h) | Ours(10.5h) | (18.3h) | Ours(7.6h) | (15.5h) | Ours(6.2h) |
| Faverage1 | 0.840 | 0.855 | 0.774 | 0.776 | 0.804 | 0.810 | | --- | --- | --- | --- | --- | --- | --- | | Fbuilding1 | 0.823 | 0.837 | 0.821 | 0.822 | 0.824 | 0.823 | | Froad1 | 0.821 | 0.843 | 0.741 | 0.746 | 0.695 | 0.707 | | Fbackground1 | 0.849 | 0.861 | 0.754 | 0.754 | 0.894 | 0.891 |
1
| | Chicago | Paris | Zurich | | | | | --- | --- | --- | --- | --- | --- | --- | | | (15.7h) | Ours(10.5h) | (18.3h) | Ours(7.6h) | (15.5h) | Ours(6.2h) |
| 1016CNNa | 150 | 122 | 13 | 28 | 0.904 | 0.813 | 0.856 | 242 | 211 | 12 | 31 | 0.946 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1021ABCa | 175 | 154 | 22 | 21 | 0.875 | 0.88 | 0.877 | 240 | 227 | 14 | 13 | 0.942 | | 1101CNNa | 204 | 187 | 13 | 17 | 0.935 | 0.917 | 0.926 | 191 | 180 | 12 | 11 | 0.938 | | 1109ABCa | 170 | 159 | 12 | 11 | 0.93 | 0.935 | 0.933 | 257 | 241 | 11 | 16 | 0.956 | | 1123CNNa | 126 | 99 | 32 | 27 | 0.756 | 0.786 | 0.77 | 236 | 206 | 8 | 30 | 0.963 | | 1126ABCa | 189 | 179 | 16 | 10 | 0.918 | 0.947 | 0.932 | 273 | 260 | 14 | 13 | 0.949 | | 1208CNNa | 137 | 117 | 22 | 20 | 0.842 | 0.854 | 0.848 | 212 | 192 | 17 | 20 | 0.919 | | 1210ABCa | 159 | 148 | 21 | 11 | 0.876 | 0.931 | 0.902 | 271 | 251 | 7 | 20 | 0.973 | | 1216CNNa | 153 | 137 | 25 | 16 | 0.846 | 0.895 | 0.87 | 197 | 184 | 21 | 13 | 0.898 | | 1221ABCa | 195 | 168 | 18 | 27 | 0.903 | 0.862 | 0.882 | 217 | 195 | 13 | 22 | 0.938 | | Total | 2031 | 1796 | 226 | 235 | 0.888 | 0.884 | 0.886 | 2775 | 2547 | 160 | 228 | 0.941 |
0
| KernelMethods | RBF | Linear | | | | --- | --- | --- | --- | --- | | Method | WSS-WR | WSS3 | WSS-WR | WSS3 | | MPG | 6.9927 | 6.4602 | 12.325 | 12.058 | | MG | 0.01533 | 0.014618 | 0.02161 | 0.02138 |
| KernelMethods | Polynomial | Sigmoid | | | | --- | --- | --- | --- | --- | | Method | WSS-WR | WSS3 | WSS-WR | WSS3 | | MPG | 0.25 | 0.5 | 14.669 | 14.22 | | MG | 0.019672 | 0.018778 | 0.023228 | 0.023548 |
1
| KernelMethods | RBF | Linear | | | | --- | --- | --- | --- | --- | | Method | WSS-WR | WSS3 | WSS-WR | WSS3 | | MPG | 6.9927 | 6.4602 | 12.325 | 12.058 | | MG | 0.01533 | 0.014618 | 0.02161 | 0.02138 |
| Method | LFW-a4× | LFW-a8× | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | PSNR | SSIM | IFC | WPSNR | NQM | PSNR | SSIM | IFC | WPSNR | NQM | | | NN | 24.16 | 0.687 | 1.23 | 33.55 | 7.99 | 20.56 | 0.441 | 0.38 | 27.22 | 4.43 | | Bicubic | 26.62 | 0.796 | 1.84 | 34.61 | 10.72 | 22.16 | 0.575 | 0.77 | 28.38 | 6.13 | | KK | 27.53 | 0.826 | 2.07 | 36.04 | 11.55 | 22.75 | 0.603 | 0.84 | 29.14 | 6.70 | | SRCNN | 27.55 | 0.827 | 2.03 | 36.12 | 11.55 | 22.74 | 0.607 | 0.83 | 29.08 | 6.66 | | LSF | 22.98 | 0.601 | 0.80 | 29.95 | 7.01 | 20.02 | 0.434 | 0.41 | 26.44 | 4.01 | | MZQ | 26.36 | 0.784 | 1.61 | 34.10 | 10.69 | 22.64 | 0.621 | 0.83 | 29.11 | 6.89 | | YLY | 25.52 | 0.750 | 1.54 | 33.62 | 9.51 | 20.80 | 0.500 | 0.59 | 27.30 | 4.82 | | BCCNN | 26.63 | 0.800 | 1.81 | 34.57 | 10.90 | 22.72 | 0.627 | 0.90 | 29.08 | 6.89 | | GLN | 28.82 | 0.863 | 2.35 | 37.80 | 13.01 | 24.07 | 0.688 | 1.12 | 30.75 | 8.19 |
0
| KernelMethods | RBF | Linear | | | | --- | --- | --- | --- | --- | | Method | WSS-WR | WSS3 | WSS-WR | WSS3 | | MPG | 6.9927 | 6.4602 | 12.325 | 12.058 | | MG | 0.01533 | 0.014618 | 0.02161 | 0.02138 | | KernelMethods | Polynomial | Sigmoid | | |
| Method | WSS-WR | WSS3 | WSS-WR | WSS3 | | --- | --- | --- | --- | --- | | MPG | 0.25 | 0.5 | 14.669 | 14.22 | | MG | 0.019672 | 0.018778 | 0.023228 | 0.023548 |
1
| KernelMethods | RBF | Linear | | | | --- | --- | --- | --- | --- | | Method | WSS-WR | WSS3 | WSS-WR | WSS3 | | MPG | 6.9927 | 6.4602 | 12.325 | 12.058 | | MG | 0.01533 | 0.014618 | 0.02161 | 0.02138 | | KernelMethods | Polynomial | Sigmoid | | |
| KK | 27.53 | 0.826 | 2.07 | 36.04 | 11.55 | 22.75 | 0.603 | 0.84 | 29.14 | 6.70 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | SRCNN | 27.55 | 0.827 | 2.03 | 36.12 | 11.55 | 22.74 | 0.607 | 0.83 | 29.08 | 6.66 | | LSF | 22.98 | 0.601 | 0.80 | 29.95 | 7.01 | 20.02 | 0.434 | 0.41 | 26.44 | 4.01 | | MZQ | 26.36 | 0.784 | 1.61 | 34.10 | 10.69 | 22.64 | 0.621 | 0.83 | 29.11 | 6.89 | | YLY | 25.52 | 0.750 | 1.54 | 33.62 | 9.51 | 20.80 | 0.500 | 0.59 | 27.30 | 4.82 | | BCCNN | 26.63 | 0.800 | 1.81 | 34.57 | 10.90 | 22.72 | 0.627 | 0.90 | 29.08 | 6.89 | | GLN | 28.82 | 0.863 | 2.35 | 37.80 | 13.01 | 24.07 | 0.688 | 1.12 | 30.75 | 8.19 |
0
| DataSet | MPEG-7 | | --- | --- | | CSS | 75.44 |
| Visualparts | 76.45 | | --- | --- | | SC | 76.51 | | CPDH | 76.56 | | Aligningcurves | 78.16 | | ProposedApproach | 79.38 | | SSC | 79.92 |
1
| DataSet | MPEG-7 | | --- | --- | | CSS | 75.44 |
| | DISFA | BP4D | | --- | --- | --- | | #seqs | 27 | 328 | | #frames | 130,814 | 144,682 | | #activeframes | 56,356 | 117,075 | | #AU | 10 | 12 | | labelcardinality | 3.04 | 4.05 | | labeldensity | 4.05 | 0.22 |
0
| DataSet | MPEG-7 | | --- | --- | | CSS | 75.44 | | Visualparts | 76.45 | | SC | 76.51 | | CPDH | 76.56 |
| Aligningcurves | 78.16 | | --- | --- | | ProposedApproach | 79.38 | | SSC | 79.92 |
1
| DataSet | MPEG-7 | | --- | --- | | CSS | 75.44 | | Visualparts | 76.45 | | SC | 76.51 | | CPDH | 76.56 |
| #activeframes | 56,356 | 117,075 | | --- | --- | --- | | #AU | 10 | 12 | | labelcardinality | 3.04 | 4.05 | | labeldensity | 4.05 | 0.22 |
0
| Method | MOTA↑ | MOTP↑ | FP↓ | FN↓ | IDSw.↓ | detector | | --- | --- | --- | --- | --- | --- | --- | | SOT+MOT(priv) | 67.3 | 81.2 | 5338 | 30266 | 529 | private | | MOT(priv) | 67.0 | 81.3 | 5259 | 30626 | 524 | private |
| SOT+MOT | 41.9 | 77.4 | 4235 | 59757 | 198 | public | | --- | --- | --- | --- | --- | --- | --- | | SOT(templatematching)+MOT | 41.7 | 77.8 | 4201 | 59954 | 174 | public | | MOT | 38.1 | 78.1 | 5014 | 63121 | 249 | public |
1
| Method | MOTA↑ | MOTP↑ | FP↓ | FN↓ | IDSw.↓ | detector | | --- | --- | --- | --- | --- | --- | --- | | SOT+MOT(priv) | 67.3 | 81.2 | 5338 | 30266 | 529 | private | | MOT(priv) | 67.0 | 81.3 | 5259 | 30626 | 524 | private |
| PRI↑ | VoI↓ | BDE↓ | GCE↓ | | | --- | --- | --- | --- | --- | | NCut | 0.73931 | 2.9139 | 17.1560 | 0.2232 | | CTM | 0.7796 | 6.2187 | 19.1981 | 0.3647 | | HFEM | 0.7769 | 2.3067 | 10.6700 | 0.2215 | | MeanShift | 0.7769 | 4.3173 | 13.1616 | 0.5811 | | Proposedapproach | 0.7627 | 3.8036 | 10.1594 | 0.4484 |
0
| Method | MOTA↑ | MOTP↑ | FP↓ | FN↓ | IDSw.↓ | detector | | --- | --- | --- | --- | --- | --- | --- | | SOT+MOT(priv) | 67.3 | 81.2 | 5338 | 30266 | 529 | private |
| MOT(priv) | 67.0 | 81.3 | 5259 | 30626 | 524 | private | | --- | --- | --- | --- | --- | --- | --- | | SOT+MOT | 41.9 | 77.4 | 4235 | 59757 | 198 | public | | SOT(templatematching)+MOT | 41.7 | 77.8 | 4201 | 59954 | 174 | public | | MOT | 38.1 | 78.1 | 5014 | 63121 | 249 | public |
1
| Method | MOTA↑ | MOTP↑ | FP↓ | FN↓ | IDSw.↓ | detector | | --- | --- | --- | --- | --- | --- | --- | | SOT+MOT(priv) | 67.3 | 81.2 | 5338 | 30266 | 529 | private |
| MeanShift | 0.7769 | 4.3173 | 13.1616 | 0.5811 | | --- | --- | --- | --- | --- | | Proposedapproach | 0.7627 | 3.8036 | 10.1594 | 0.4484 |
0
| #ofCPUCores | #ofGPUs | | --- | --- | | 299,008 | 18688 |
| 102,400 | 7,168 | | --- | --- | | 55,680 | 4,640 | | 17,984 | 4,258 |
1
| #ofCPUCores | #ofGPUs | | --- | --- | | 299,008 | 18688 |
| (a)Numberofrenderedviews | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | | n | 200 | 500 | 1k | 2k | 5k | 10k | 86k | | AP | 29.8 | 34.2 | 35.3 | 38.7 | 40.2 | 42.0 | 44.0 | | (b)NumberofCADmodels | | | | | | | | | n | 5 | 10 | 20 | 40 | 80 | 160 | 1393 | | AP | 17.6 | 25.0 | 29.3 | 32.8 | 33.8 | 38.1 | 44.0 |
0
| #ofCPUCores | #ofGPUs | | --- | --- | | 299,008 | 18688 | | 102,400 | 7,168 |
| 55,680 | 4,640 | | --- | --- | | 17,984 | 4,258 |
1
| #ofCPUCores | #ofGPUs | | --- | --- | | 299,008 | 18688 | | 102,400 | 7,168 |
| (b)NumberofCADmodels | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | | n | 5 | 10 | 20 | 40 | 80 | 160 | 1393 | | AP | 17.6 | 25.0 | 29.3 | 32.8 | 33.8 | 38.1 | 44.0 |
0
| KNN | SVM-RBF | DT | RF | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Dataset | AP | RE | AP | RE | AP | RE | AP | RE | | Digits08 | 0.89 | 0.96 | 0.97 | 0.89 | 0.87 | 0.63 | 0.85 | 0.48 | | Credit | 0.96 | 0.78 | 0.94 | 0.53 | 0.79 | 0.42 | 0.79 | 0.33 | | Cancer | 0.99 | 0.99 | 0.99 | 0.99 | 0.97 | 0.89 | 0.99 | 0.98 | | Qsar | 1 | 0.99 | 0.99 | 0.99 | 0.96 | 0.76 | 0.99 | 0.99 | | Sonar | 0.99 | 0.98 | 1 | 1 | 0.97 | 0.62 | 0.99 | 0.95 |
| Theorem | 0.97 | 0.813 | 0.95 | 0.5 | 0.95 | 0.79 | 0.62 | 0.78 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Diabetes | 0.99 | 0.935 | 0.99 | 0.9 | 0.83 | 0.63 | 0.88 | 0.61 | | Spambase | 0.93 | 0.99 | 0.48 | 0.84 | 0.08 | 0.11 | 0.99 | 0.98 | | KDD99 | 0.99 | 0.93 | 1 | 0.99 | 0.89 | 0.54 | 0.92 | 0.27 | | CAPTCHA | 0.99 | 0.92 | 0.99 | 0.92 | 0.97 | 0.83 | 0.93 | 0.89 |
1
| KNN | SVM-RBF | DT | RF | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Dataset | AP | RE | AP | RE | AP | RE | AP | RE | | Digits08 | 0.89 | 0.96 | 0.97 | 0.89 | 0.87 | 0.63 | 0.85 | 0.48 | | Credit | 0.96 | 0.78 | 0.94 | 0.53 | 0.79 | 0.42 | 0.79 | 0.33 | | Cancer | 0.99 | 0.99 | 0.99 | 0.99 | 0.97 | 0.89 | 0.99 | 0.98 | | Qsar | 1 | 0.99 | 0.99 | 0.99 | 0.96 | 0.76 | 0.99 | 0.99 | | Sonar | 0.99 | 0.98 | 1 | 1 | 0.97 | 0.62 | 0.99 | 0.95 |
| kNN | SVM-RBF | DT | RF | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Dataset | AP | RE | AP | RE | AP | RE | AP | RE | | Digits08 | 0.89 | 0.96 | 0.97 | 0.89 | 0.87 | 0.63 | 0.85 | 0.48 | | Credit | 0.96 | 0.78 | 0.94 | 0.53 | 0.79 | 0.42 | 0.79 | 0.33 | | Cancer | 0.99 | 0.99 | 0.99 | 0.99 | 0.97 | 0.89 | 0.99 | 0.98 | | Qsar | 1 | 0.99 | 0.99 | 0.99 | 0.96 | 0.76 | 0.99 | 0.99 | | Sonar | 0.99 | 0.98 | 1 | 1 | 0.97 | 0.62 | 0.99 | 0.95 | | Theorem | 0.97 | 0.813 | 0.95 | 0.5 | 0.95 | 0.79 | 0.62 | 0.78 | | Diabetes | 0.99 | 0.935 | 0.99 | 0.9 | 0.83 | 0.63 | 0.88 | 0.61 | | Spambase | 0.93 | 0.99 | 0.48 | 0.84 | 0.08 | 0.11 | 0.99 | 0.98 | | KDD99 | 0.99 | 0.93 | 1 | 0.99 | 0.89 | 0.54 | 0.92 | 0.27 | | Captcha | 0.99 | 0.92 | 0.99 | 0.92 | 0.97 | 0.83 | 0.93 | 0.89 |
0
| KNN | SVM-RBF | DT | RF | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Dataset | AP | RE | AP | RE | AP | RE | AP | RE | | Digits08 | 0.89 | 0.96 | 0.97 | 0.89 | 0.87 | 0.63 | 0.85 | 0.48 | | Credit | 0.96 | 0.78 | 0.94 | 0.53 | 0.79 | 0.42 | 0.79 | 0.33 | | Cancer | 0.99 | 0.99 | 0.99 | 0.99 | 0.97 | 0.89 | 0.99 | 0.98 | | Qsar | 1 | 0.99 | 0.99 | 0.99 | 0.96 | 0.76 | 0.99 | 0.99 | | Sonar | 0.99 | 0.98 | 1 | 1 | 0.97 | 0.62 | 0.99 | 0.95 | | Theorem | 0.97 | 0.813 | 0.95 | 0.5 | 0.95 | 0.79 | 0.62 | 0.78 | | Diabetes | 0.99 | 0.935 | 0.99 | 0.9 | 0.83 | 0.63 | 0.88 | 0.61 |
| Spambase | 0.93 | 0.99 | 0.48 | 0.84 | 0.08 | 0.11 | 0.99 | 0.98 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | KDD99 | 0.99 | 0.93 | 1 | 0.99 | 0.89 | 0.54 | 0.92 | 0.27 | | CAPTCHA | 0.99 | 0.92 | 0.99 | 0.92 | 0.97 | 0.83 | 0.93 | 0.89 |
1
| KNN | SVM-RBF | DT | RF | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Dataset | AP | RE | AP | RE | AP | RE | AP | RE | | Digits08 | 0.89 | 0.96 | 0.97 | 0.89 | 0.87 | 0.63 | 0.85 | 0.48 | | Credit | 0.96 | 0.78 | 0.94 | 0.53 | 0.79 | 0.42 | 0.79 | 0.33 | | Cancer | 0.99 | 0.99 | 0.99 | 0.99 | 0.97 | 0.89 | 0.99 | 0.98 | | Qsar | 1 | 0.99 | 0.99 | 0.99 | 0.96 | 0.76 | 0.99 | 0.99 | | Sonar | 0.99 | 0.98 | 1 | 1 | 0.97 | 0.62 | 0.99 | 0.95 | | Theorem | 0.97 | 0.813 | 0.95 | 0.5 | 0.95 | 0.79 | 0.62 | 0.78 | | Diabetes | 0.99 | 0.935 | 0.99 | 0.9 | 0.83 | 0.63 | 0.88 | 0.61 |
| KDD99 | 0.99 | 0.93 | 1 | 0.99 | 0.89 | 0.54 | 0.92 | 0.27 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Captcha | 0.99 | 0.92 | 0.99 | 0.92 | 0.97 | 0.83 | 0.93 | 0.89 |
0
| Conv.Layers | ODS | OIS | AP | | --- | --- | --- | --- | | st<br>1 | 0.66 | 0.68 | 0.69 | | 2 | 0.71 | 0.74 | 0.76 |
| 3 | 0.74 | 0.75 | 0.79 | | --- | --- | --- | --- | | 4 | 0.74 | 0.76 | 0.79 | | 5 | 0.73 | 0.74 | 0.77 | | All | 0.75 | 0.77 | 0.81 |
1
| Conv.Layers | ODS | OIS | AP | | --- | --- | --- | --- | | st<br>1 | 0.66 | 0.68 | 0.69 | | 2 | 0.71 | 0.74 | 0.76 |
| Layer | AVGPower[mW] | ExecTime[ms] | L3-L2Time[ms] | | --- | --- | --- | --- | | conv1+pool | 89.01 | 12.95 | 0.02 | | ReLU | 52.07 | 0.46 | — | | conv2+ReLU | 87.96 | 11.12 | 0.13 | | conv3 | 77.46 | 11.85 | 0.13 | | conv4 | 83.56 | 5.49 | 0.02 | | add | 37.75 | 0.12 | — | | ReLU | 36.81 | 0.12 | — | | conv5+ReLU | 78.10 | 8.34 | 0.26 | | conv6 | 91.72 | 9.35 | 0.51 | | conv7 | 66.53 | 2.08 | 0.04 | | add | 34.98 | 0.12 | — | | ReLU | 34.01 | 0.11 | — | | conv8+ReLU | 87.49 | 6.37 | 1.01 | | conv9 | 89.67 | 11.91 | 2.02 | | conv10 | 66.00 | 2.59 | 0.12 | | add+ReLU | 34.30 | 0.11 | — | | fully1 | 30.76 | 0.04 | 0.09 | | fully2 | 36.74 | 0.04 | 0.09 |
0
| Conv.Layers | ODS | OIS | AP | | --- | --- | --- | --- | | st<br>1 | 0.66 | 0.68 | 0.69 | | 2 | 0.71 | 0.74 | 0.76 |
| 3 | 0.74 | 0.75 | 0.79 | | --- | --- | --- | --- | | 4 | 0.74 | 0.76 | 0.79 | | 5 | 0.73 | 0.74 | 0.77 | | All | 0.75 | 0.77 | 0.81 |
1
| Conv.Layers | ODS | OIS | AP | | --- | --- | --- | --- | | st<br>1 | 0.66 | 0.68 | 0.69 | | 2 | 0.71 | 0.74 | 0.76 |
| add | 37.75 | 0.12 | — | | --- | --- | --- | --- | | ReLU | 36.81 | 0.12 | — | | conv5+ReLU | 78.10 | 8.34 | 0.26 | | conv6 | 91.72 | 9.35 | 0.51 | | conv7 | 66.53 | 2.08 | 0.04 | | add | 34.98 | 0.12 | — | | ReLU | 34.01 | 0.11 | — | | conv8+ReLU | 87.49 | 6.37 | 1.01 | | conv9 | 89.67 | 11.91 | 2.02 | | conv10 | 66.00 | 2.59 | 0.12 | | add+ReLU | 34.30 | 0.11 | — | | fully1 | 30.76 | 0.04 | 0.09 | | fully2 | 36.74 | 0.04 | 0.09 |
0
| Parameter | ValueRange(Average) | | --- | --- | | STENCILPATTERN<br>STENCILRADIUS | Allthree<br>0−2 |
| NUMCOMPILB<br>NUMCOMPEP | 5−44(19)<br>1−48(23) | | --- | --- | | NUMCOALACCESSESILB<br>NUMCOALACCESSESEP | 0−13(3)<br>0−13(5) | | NUMUNCOALACCESSESILB<br>NUMUNCOALACCESSESEP | 0−4(0.8)<br>0−4(0.8) |
1
| Parameter | ValueRange(Average) | | --- | --- | | STENCILPATTERN<br>STENCILRADIUS | Allthree<br>0−2 |
| σ | ReLD | PCP-LD | NCRPCA-LD | GRASTA-LD | | --- | --- | --- | --- | --- | | 25 | 35.00,32.78(73.54) | 34.92,32.84(198.87) | 33.34,31.98(101.78) | 30.45,28.11(59.43) | | 30 | 34.51,32.68(73.33) | 34.42,32.60(185.47) | 32.53,31.56(106.30) | 29.40,26.89(58.76) | | 50 | 33.08,32.27(73.14) | 32.93,31.65(195.77) | 30.48,30.09(128.35) | 25.33,23.97(58.23) | | 70 | 29.25,31.79(69.77) | 29.17,30.67(197.94) | 27.97,29.63(133.53) | 21.89,21.81(55.45) |
0
| Parameter | ValueRange(Average) | | --- | --- | | STENCILPATTERN<br>STENCILRADIUS | Allthree<br>0−2 |
| NUMCOMPILB<br>NUMCOMPEP | 5−44(19)<br>1−48(23) | | --- | --- | | NUMCOALACCESSESILB<br>NUMCOALACCESSESEP | 0−13(3)<br>0−13(5) | | NUMUNCOALACCESSESILB<br>NUMUNCOALACCESSESEP | 0−4(0.8)<br>0−4(0.8) |
1
| Parameter | ValueRange(Average) | | --- | --- | | STENCILPATTERN<br>STENCILRADIUS | Allthree<br>0−2 |
| 50 | 33.08,32.27(73.14) | 32.93,31.65(195.77) | 30.48,30.09(128.35) | 25.33,23.97(58.23) | | --- | --- | --- | --- | --- | | 70 | 29.25,31.79(69.77) | 29.17,30.67(197.94) | 27.97,29.63(133.53) | 21.89,21.81(55.45) |
0
| 97.88 | | --- | | 97.59 |
| 94.51<br>92.60 | | --- | | 0.236 | | 84.6 |
1
| 97.88 | | --- | | 97.59 |
| 97.88 | | --- | | 97.59 | | 94.51<br>92.60 | | 0.236 | | 84.6 |
0
| 97.88 | | --- | | 97.59 | | 94.51<br>92.60 |
| 0.236 | | --- | | 84.6 |
1
| 97.88 | | --- | | 97.59 | | 94.51<br>92.60 |
| 94.51<br>92.60 | | --- | | 0.236 | | 84.6 |
0
| DataSet | Sentences# | Tokens# | | --- | --- | --- | | Training | 14,987 | 203,621 |
| Develop | 3,466 | 51,362 | | --- | --- | --- | | Test | 3,684 | 46,435 | | #oftagtypes(IOBESscheme) | 17 | |
1
| DataSet | Sentences# | Tokens# | | --- | --- | --- | | Training | 14,987 | 203,621 |
| DataSet | WSJsec.IDs | Sentences# | Tokens# | | --- | --- | --- | --- | | Training | 15-18 | 8,936 | 211,727 | | Develop | N/A | N/A | N/A | | Test | 20 | 2,012 | 47,377 | | #oftagtypes(IOBESscheme) | 42 | | |
0
| DataSet | Sentences# | Tokens# | | --- | --- | --- | | Training | 14,987 | 203,621 | | Develop | 3,466 | 51,362 |
| Test | 3,684 | 46,435 | | --- | --- | --- | | #oftagtypes(IOBESscheme) | 17 | |
1
| DataSet | Sentences# | Tokens# | | --- | --- | --- | | Training | 14,987 | 203,621 | | Develop | 3,466 | 51,362 |
| Develop | N/A | N/A | N/A | | --- | --- | --- | --- | | Test | 20 | 2,012 | 47,377 | | #oftagtypes(IOBESscheme) | 42 | | |
0